A checkpoint-oriented cell cycle simulation model

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Increased recombinant adeno-associated virus production by HEK293 cells using small molecule chemical additives

Recombinant adeno-associated virus (rAAV) has established itself as a highly efficacious gene delivery vector with a well characterised safety profile allowing broad clinical application. Recent successes in rAAV-mediated gene therapy clinical trials will continue to drive demand for improved rAAV production processes to reduce costs. Here, we demonstrate that small molecule bioactive chemical additives can significantly increase recombinant AAV vector production by human embryonic kidney (HEK) cells up to three-fold. Nocodazole (an anti-mitotic agent) and M344 (a selective histone deacetylase inhibitor) were identified as positive regulators of rAAV8 genome titre in a microplate screening assay. Addition of nocodazole to triple-transfected HEK293 suspension cells producing rAAV arrested cells in G2/M phase, increased average cell volume and reduced viable cell density relative to untreated rAAV producing cells at harvest. Final crude genome vector titre from nocodazole treated cultures was >2-fold higher compared to non-treated cultures. Further investigation showed nocodazole addition to cultures to be time critical. Genome titre improvement was found to be scalable and serotype independent across two distinct rAAV serotypes, rAAV8 and rAAV9. Furthermore, a combination of M344 and nocodazole produced a positive additive effect on rAAV8 genome titre, resulting in a three-fold increase in genome titre compared to untreated cells.

Modeling the Dynamics of T-Cell Development in the Thymus

The thymus hosts the development of a specific type of adaptive immune cells called T cells. T cells orchestrate the adaptive immune response through recognition of antigen by the highly variable T-cell receptor (TCR). T-cell development is a tightly coordinated process comprising lineage commitment, somatic recombination of Tcr gene loci and selection for functional, but non-self-reactive TCRs, all interspersed with massive proliferation and cell death. Thus, the thymus produces a pool of T cells throughout life capable of responding to virtually any exogenous attack while preserving the body through self-tolerance. The thymus has been of considerable interest to both immunologists and theoretical biologists due to its multi-scale quantitative properties, bridging molecular binding, population dynamics and polyclonal repertoire specificity. Here, we review experimental strategies aimed at revealing quantitative and dynamic properties of T-cell development and how they have been implemented in mathematical modeling strategies that were reported to help understand the flexible dynamics of the highly dividing and dying thymic cell populations. Furthermore, we summarize the current challenges to estimating in vivo cellular dynamics and to reaching a next-generation multi-scale picture of T-cell development.

Rck of Salmonella Typhimurium Delays the Host Cell Cycle to Facilitate Bacterial Invasion

Salmonella Typhimurium expresses on its outer membrane the protein Rck which interacts with the epidermal growth factor receptor (EGFR) of the plasma membrane of the targeted host cells. This interaction activates signaling pathways, leading to the internalization of Salmonella. Since EGFR plays a key role in cell proliferation, we sought to determine the influence of Rck mediated infection on the host cell cycle. By analyzing the DNA content of uninfected and infected cells using flow cytometry, we showed that the Rck-mediated infection induced a delay in the S-phase (DNA replication phase) of the host cell cycle, independently of bacterial internalization. We also established that this Rck-dependent delay in cell cycle progression was accompanied by an increased level of host DNA double strand breaks and activation of the DNA damage response. Finally, we demonstrated that the S-phase environment facilitated Rck-mediated bacterial internalization. Consequently, our results suggest that Rck can be considered as a cyclomodulin with a genotoxic activity.

Sequential adjustment of cytotoxic T lymphocyte densities improves efficacy in controlling tumor growth

Understanding the human cytotoxic T lymphocyte (CTL) biology is crucial to develop novel strategies aiming at maximizing their lytic capacity against cancer cells. Here we introduce an agent-based model, calibrated on population-scale experimental data that allows quantifying human CTL per capita killing. Our model highlights higher individual CTL killing capacity at lower CTL densities and fits experimental data of human melanoma cell killing. The model allows extending the analysis over prolonged time frames, difficult to investigate experimentally, and reveals that initial high CTL densities hamper efficacy to control melanoma growth. Computational analysis forecasts that sequential addition of fresh CTL cohorts improves tumor growth control. In vivo experimental data, obtained in a mouse melanoma model, confirm this prediction. Taken together, our results unveil the impact that sequential adjustment of cellular densities has on enhancing CTL efficacy over long-term confrontation with tumor cells. In perspective, they can be instrumental to refine CTL-based therapeutic strategies aiming at controlling tumor growth.